Body motion tracking has a wide range of applications extending from medicine to entertainment. For example, body motion tracking has become a popular method for interfacing with virtual reality systems. Personal communication devices, such as smart phones, may use motion tracking system to detect user interaction with the device. Within the field of biomedical engineering, data analysis of body motion is one component used for understanding kinematics and the kinetics of the human body. Once the kinematics of a patient are understood, this knowledge may be used to design prosthetics, implants, and diagnostic instruments. Known body motion tracking methodologies include capturing body motion by collecting data from bio-imaging units that use ionizing radiation to image the patient, and from motion tracking devices attached to the patient that capture motion directly. This data may then be analyzed to determine design parameters for the device in question.
Although normal human body motion is well studied, there remain gaps within this knowledge base with respect to correlating abnormal motions to clinical diagnosis. One of the obstacles to more extensive use of motion tracking using known methodologies is that conventional systems are bulky and not always available in hospital. These systems typically require specially-trained technicians, making day-to-day diagnostic use impractical. Systems that use ionizing radiation may also be undesirable due to potential adverse health effects resulting from exposure the radiation used to image the patient.
One type of motion tracking device is an Inertial Measurement Unit (IMU). IMUS are configured to detect motion based on the effects of acceleration on a sensor. Generally, an IMU includes multiple inertial measuring sensors, such as accelerometers and/or gyroscopes that allow the position of the IMU to be determined without an external reference. Conventional types of IMU systems vary in accuracy and size. For example, micro-machined micro-electro-mechanical system (“MEMS”) based sensors coupled with integrated circuit technology have allowed IMUS to be miniaturized. However, the static accuracy of MEMS-based IMUS is limited to about 0.4 degrees in orientation and about 4 degrees under cyclic motion.
Thus, while conventional MEMS-based IMUS may have potential for biomedical implementations, the resolution/accuracy of MEMS-based IMUS remains relatively low. More specifically, currently, commercially-available IMU systems have pre-determined and limited operational dynamic range that is not tailored and optimized for human body motion tracking. Conventional IMU systems are thus not suitable for determining patient motion because they do not meet the resolution and dynamic range requirements, which vary depending on the activities being monitored.
As a result, there remains a need for improved motion tracking systems, apparatuses, and methods that are easy to use, highly accurate, and low in cost, with high mobility, and that avoid using radiation-based imaging technologies.